Ellen B Mendelson1. 1. 1 Feinberg School of Medicine, Northwestern University, Lynn Sage Breast Imaging Center, Prentice Hospital-Northwestern Memorial, Suite 4-2304, 250 E Superior St, Chicago, IL 60611.
Abstract
OBJECTIVE: The purpose of this article is to discuss potential applications of artificial intelligence (AI) in breast imaging and limitations that may slow or prevent its adoption. CONCLUSION: The algorithms of AI for workflow improvement and outcome analyses are advancing. Using imaging data of high quality and quantity, AI can support breast imagers in diagnosis and patient management, but AI cannot yet be relied on or be responsible for physicians' decisions that may affect survival. Education in AI is urgently needed for physicians.
OBJECTIVE: The purpose of this article is to discuss potential applications of artificial intelligence (AI) in breast imaging and limitations that may slow or prevent its adoption. CONCLUSION: The algorithms of AI for workflow improvement and outcome analyses are advancing. Using imaging data of high quality and quantity, AI can support breast imagers in diagnosis and patient management, but AI cannot yet be relied on or be responsible for physicians' decisions that may affect survival. Education in AI is urgently needed for physicians.
Entities:
Keywords:
artificial intelligence in breast imaging; artificial intelligence in radiology; artificial neural networks; computer-aided detection and diagnosis; machine and deep learning
Authors: Gábor Forrai; Eszter Kovács; Éva Ambrózay; Miklós Barta; Katalin Borbély; Zsolt Lengyel; Katalin Ormándi; Zoltán Péntek; Tasnádi Tünde; Éva Sebő Journal: Pathol Oncol Res Date: 2022-06-08 Impact factor: 2.874